{"id":"W7070253295","doi":"","title":"Editorial","year":2007,"lang":"en","type":"article","venue":"Open ULeth Scholarship (OPUS) (University of Lethbridge)","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Reading (process); Front (military); Government (linguistics); Period (music); Closing (real estate)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002134234,0.0001823394,0.0002385234,0.00009561422,0.0002813032,0.00007472803,0.001388217,0.0003467856,0.0001200999],"category_scores_gemma":[0.0003118287,0.0002251812,0.0001302355,0.0001921365,0.0001811557,0.00006292074,0.0008879522,0.0004941991,0.0001111047],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003498044,"about_ca_system_score_gemma":0.00013078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002933918,"about_ca_topic_score_gemma":0.0001354296,"domain_scores_codex":[0.9985998,0.0001165163,0.0002245076,0.0003273094,0.0003701132,0.0003617465],"domain_scores_gemma":[0.9986821,0.00004763067,0.0002650065,0.0005882781,0.0002352914,0.0001817273],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002403216,0.0003836341,0.08233234,0.000208951,0.0003791066,0.00005352087,0.001378799,0.000143002,0.3453843,0.002839607,0.5342233,0.03027021],"study_design_scores_gemma":[0.001866026,0.0003535176,0.03253887,0.00004370797,0.0000424213,0.00001736951,0.0005723343,0.00002976569,0.01995949,0.00008995946,0.9440722,0.0004142824],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9154472,0.0001118821,0.01384673,0.0007042985,0.0113341,0.0005978834,0.00005327857,0.00004482927,0.05785985],"genre_scores_gemma":[0.9560775,0.00006833246,0.02836533,0.0004829871,0.007979869,4.007488e-7,0.0002468495,0.00004001732,0.006738713],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4098489,"threshold_uncertainty_score":0.9182622,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01291514135910843,"score_gpt":0.2709487446016577,"score_spread":0.2580336032425493,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}